New method of linear time-frequency analysis for signal detection

Author

Lee, N. ; Huynh, Q. ; Schwartz, S.

Author_Institution

Naval Underwater Syst. Center, Newport, RI, USA

fYear

1996

fDate

18-21 Jun 1996

Firstpage

13

Lastpage

16

Abstract

Previous work on standard signal detection via linear time-frequency (TF) transforms has focused on detectors based on the standard linear TF transforms: the short-time Fourier transform (STFT), the Gabor transform, and the wavelet transform (WT). This paper examines two methods of improving linear-TF-based detection. The first method uses the Coifman-Meyer-Wickerhauser (see IEEE Transactions on Information Theory, vol.38, no.2, p.713-18, 1992) “best basis” concept for detection based on adaptive-window-length local cosine and wavelet packet transforms. The second method uses the Mallat-Zhang (see IEEE Transactions on Signal Processing, vol.41, no.12, p.3397-3415, 1993) matching pursuit algorithm for detection based on a combination of STFT and (standard) wavelet functions

Keywords

adaptive signal detection; time-frequency analysis; transforms; wavelet transforms; Gabor transform; STFT; adaptive window length; best basis concept; linear time-frequency analysis; linear time-frequency transforms; local cosine transforms; matching pursuit algorithm; short-time Fourier transform; signal detection; wavelet functions; wavelet packet transforms; wavelet transform; Detectors; Fourier transforms; Matched filters; Matching pursuit algorithms; Signal detection; Tellurium; Testing; Time frequency analysis; Wavelet packets; Wavelet transforms;

fLanguage

English

Publisher

ieee

Conference_Titel

Time-Frequency and Time-Scale Analysis, 1996., Proceedings of the IEEE-SP International Symposium on

Conference_Location

Paris

Print_ISBN

0-7803-3512-0

Type

conf

DOI

10.1109/TFSA.1996.546674

Filename

546674